The healthcare sector involves many steps to ensure efficient care for patients,such as appointment scheduling,consultation plans,online follow-up,and more.However,existing healthcare mechanisms are unable to facilita...The healthcare sector involves many steps to ensure efficient care for patients,such as appointment scheduling,consultation plans,online follow-up,and more.However,existing healthcare mechanisms are unable to facilitate a large number of patients,as these systems are centralized and hence vulnerable to various issues,including single points of failure,performance bottlenecks,and substantial monetary costs.Furthermore,these mechanisms are unable to provide an efficient mechanism for saving data against unauthorized access.To address these issues,this study proposes a blockchain-based authentication mechanism that authenticates all healthcare stakeholders based on their credentials.Furthermore,also utilize the capabilities of the InterPlanetary File System(IPFS)to store the Electronic Health Record(EHR)in a distributed way.This IPFS platform addresses not only the issue of high data storage costs on blockchain but also the issue of a single point of failure in the traditional centralized data storage model.The simulation results demonstrate that our model outperforms the benchmark schemes and provides an efficient mechanism for managing healthcare sector operations.The results show that it takes approximately 3.5 s for the smart contract to authenticate the node and provide it with the decryption key,which is ultimately used to access the data.The simulation results show that our proposed model outperforms existing solutions in terms of execution time and scalability.The execution time of our model smart contract is around 9000 transactions in just 6.5 s,while benchmark schemes require approximately 7 s for the same number of transactions.展开更多
As is known,centralized federated learning faces risks of a single point of failure and privacy breaches,and blockchain-based federated learning frameworks can address these challenges to a certain extent in recent wo...As is known,centralized federated learning faces risks of a single point of failure and privacy breaches,and blockchain-based federated learning frameworks can address these challenges to a certain extent in recent works.However,malicious clients may still illegally access the blockchain to upload malicious data or steal on-chain data.In addition,blockchain-based federated training suffers from a heavy storage burden and excessive network communication overhead.To address these issues,we propose an asynchronous,tiered federated learning storage scheme based on blockchain and IPFS.It manages the execution of federated learning tasks through smart contracts deployed on the blockchain,decentralizing the entire training process.Additionally,the scheme employs a secure and efficient blockchain-based asynchronous tiered architecture,integrating attribute-based access control technology for resource exchange between the clients and the blockchain network.It dynamically manages access control policies during training and adopts a hybrid data storage strategy combining blockchain and IPFS.Experiments with multiple sets of image classification tasks are conducted,indicating that the storage strategy used in this scheme saves nearly 50 percent of the communication overhead and significantly reduces the on-chain storage burden compared to the traditional blockchain-only storage strategy.In terms of training effectiveness,it maintains similar accuracy as centralized training and minimizes the probability of being attacked.展开更多
Proper knowledge of the nature of geomagnetic storms and their relationships with the conditions of the space environment at the outer part of the Earth's magnetosphere(bow shock nose) is essential to increase our...Proper knowledge of the nature of geomagnetic storms and their relationships with the conditions of the space environment at the outer part of the Earth's magnetosphere(bow shock nose) is essential to increase our resilience to space weather disturbances. In this article, we present an analysis of the interplanetary magnetic field(IMF) and solar wind parameters relevant to 100 geomagnetic storms in Solar Cycle 24. We revisit the relationship between the minimum disturbance storm time index(Dst_(min)), the minimum southward IMF(B_(S, min)), the maximum solar wind density(N_(SW, max)) and speed(V_(max)), and the lag time between the extrema(dT(B_(z), N),dT(B_(z), V)). We end with a regression formula that fits the data, with a coefficient of determination of 0.58, a root mean square error of 21.30 nT, and a mean absolute error of 15.87 nT. Even though more complex machine learning models can outperform this model, it serves as a theoretically sensible alternative for understanding and forecasting geomagnetic storms.展开更多
The caption of Figure 5 should be:Wind/WAVES type II burst starting around 14 MHz(∼12:05 UT,2017 September 6)and continuing down to∼100 kHz(09:00 UT,2017 September 7).The end time is marked by the short vertical lin...The caption of Figure 5 should be:Wind/WAVES type II burst starting around 14 MHz(∼12:05 UT,2017 September 6)and continuing down to∼100 kHz(09:00 UT,2017 September 7).The end time is marked by the short vertical line with its length indicating the bandwidth(70-130 kHz).The horizontal error bars signify the end time uncertainty.The vertical dashed line marks the SGRE end(06:28 UT,September 7);the horizontal dashed line represents the gamma-ray background.The shock arrival time at 1 au is labeled“SH”(Gopalswamy et al.2018).展开更多
The Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)Soft X-ray Imager(SXI)will shine a spotlight on magnetopause dynamics during magnetic reconnection.We simulate an event with a southward interplanetary magne...The Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)Soft X-ray Imager(SXI)will shine a spotlight on magnetopause dynamics during magnetic reconnection.We simulate an event with a southward interplanetary magnetic field turning and produce SXI count maps with a 5-minute integration time.By making assumptions about the magnetopause shape,we find the magnetopause standoff distance from the count maps and compare it with the one obtained directly from the magnetohydrodynamic(MHD)simulation.The root mean square deviations between the reconstructed and MHD standoff distances do not exceed 0.2 RE(Earth radius)and the maximal difference equals 0.24 RE during the 25-minute interval around the southward turning.展开更多
基金supported by the Ongoing Research Funding program(ORF-2025-636),King Saud University,Riyadh,Saudi Arabia.
文摘The healthcare sector involves many steps to ensure efficient care for patients,such as appointment scheduling,consultation plans,online follow-up,and more.However,existing healthcare mechanisms are unable to facilitate a large number of patients,as these systems are centralized and hence vulnerable to various issues,including single points of failure,performance bottlenecks,and substantial monetary costs.Furthermore,these mechanisms are unable to provide an efficient mechanism for saving data against unauthorized access.To address these issues,this study proposes a blockchain-based authentication mechanism that authenticates all healthcare stakeholders based on their credentials.Furthermore,also utilize the capabilities of the InterPlanetary File System(IPFS)to store the Electronic Health Record(EHR)in a distributed way.This IPFS platform addresses not only the issue of high data storage costs on blockchain but also the issue of a single point of failure in the traditional centralized data storage model.The simulation results demonstrate that our model outperforms the benchmark schemes and provides an efficient mechanism for managing healthcare sector operations.The results show that it takes approximately 3.5 s for the smart contract to authenticate the node and provide it with the decryption key,which is ultimately used to access the data.The simulation results show that our proposed model outperforms existing solutions in terms of execution time and scalability.The execution time of our model smart contract is around 9000 transactions in just 6.5 s,while benchmark schemes require approximately 7 s for the same number of transactions.
基金supported by the National Natural Science Foundation of China(Grant No.52331012)the Natural Science Foundation of Shanghai Municipality(Grant No.21ZR1426500)the Program for Cultivation of Graduate Students’Top-notch Innovative Talents of Shanghai Maritime University(Grant No.2023YBR007).
文摘As is known,centralized federated learning faces risks of a single point of failure and privacy breaches,and blockchain-based federated learning frameworks can address these challenges to a certain extent in recent works.However,malicious clients may still illegally access the blockchain to upload malicious data or steal on-chain data.In addition,blockchain-based federated training suffers from a heavy storage burden and excessive network communication overhead.To address these issues,we propose an asynchronous,tiered federated learning storage scheme based on blockchain and IPFS.It manages the execution of federated learning tasks through smart contracts deployed on the blockchain,decentralizing the entire training process.Additionally,the scheme employs a secure and efficient blockchain-based asynchronous tiered architecture,integrating attribute-based access control technology for resource exchange between the clients and the blockchain network.It dynamically manages access control policies during training and adopts a hybrid data storage strategy combining blockchain and IPFS.Experiments with multiple sets of image classification tasks are conducted,indicating that the storage strategy used in this scheme saves nearly 50 percent of the communication overhead and significantly reduces the on-chain storage burden compared to the traditional blockchain-only storage strategy.In terms of training effectiveness,it maintains similar accuracy as centralized training and minimizes the probability of being attacked.
文摘Proper knowledge of the nature of geomagnetic storms and their relationships with the conditions of the space environment at the outer part of the Earth's magnetosphere(bow shock nose) is essential to increase our resilience to space weather disturbances. In this article, we present an analysis of the interplanetary magnetic field(IMF) and solar wind parameters relevant to 100 geomagnetic storms in Solar Cycle 24. We revisit the relationship between the minimum disturbance storm time index(Dst_(min)), the minimum southward IMF(B_(S, min)), the maximum solar wind density(N_(SW, max)) and speed(V_(max)), and the lag time between the extrema(dT(B_(z), N),dT(B_(z), V)). We end with a regression formula that fits the data, with a coefficient of determination of 0.58, a root mean square error of 21.30 nT, and a mean absolute error of 15.87 nT. Even though more complex machine learning models can outperform this model, it serves as a theoretically sensible alternative for understanding and forecasting geomagnetic storms.
文摘The caption of Figure 5 should be:Wind/WAVES type II burst starting around 14 MHz(∼12:05 UT,2017 September 6)and continuing down to∼100 kHz(09:00 UT,2017 September 7).The end time is marked by the short vertical line with its length indicating the bandwidth(70-130 kHz).The horizontal error bars signify the end time uncertainty.The vertical dashed line marks the SGRE end(06:28 UT,September 7);the horizontal dashed line represents the gamma-ray background.The shock arrival time at 1 au is labeled“SH”(Gopalswamy et al.2018).
基金support from the UK Space Agency under Grant Number ST/T002964/1partly supported by the International Space Science Institute(ISSI)in Bern,through ISSI International Team Project Number 523(“Imaging the Invisible:Unveiling the Global Structure of Earth’s Dynamic Magnetosphere”)。
文摘The Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)Soft X-ray Imager(SXI)will shine a spotlight on magnetopause dynamics during magnetic reconnection.We simulate an event with a southward interplanetary magnetic field turning and produce SXI count maps with a 5-minute integration time.By making assumptions about the magnetopause shape,we find the magnetopause standoff distance from the count maps and compare it with the one obtained directly from the magnetohydrodynamic(MHD)simulation.The root mean square deviations between the reconstructed and MHD standoff distances do not exceed 0.2 RE(Earth radius)and the maximal difference equals 0.24 RE during the 25-minute interval around the southward turning.
